• Management & Information Systems Review
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• v.35 no.4
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• pp.1-19
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• 2016

The researchers in strategic management have focused on identifying the effects of CEO's demographic characteristics and experience on the strategic choices and performance of firms. On the other hand, they have failed to identifying the effects of CEO's psychological characteristics on them because of the difficulties over data collection and measurement for variables. To overcome this limitation of prior researches, this study is designed to achieve two specific objectives. The first is to examine the effect of CEO narcissism on diversification strategy and performance of listed corporations on Korean securities market in an economic downturn. The other is to examine the moderating effects of various corporate governance systems that are related to board and/or ownership structures on those relationships. The empirical setting for this study was drawn from a multi-year(2011~2014) sample of large listed corporations in Korean securities market. To achieve the objectives, the hypotheses of research are analyzed by implementing multiple regression analyses in two separate models. The results of these analyses show that CEO narcissism is positively related to the diversification of listed large corporations in Korean securities market. Regrading the moderating effects, the stake of institutional investors weakens the positive relationship between CEO narcissism and firm's diversification. The findings of this research imply that CEO narcissism can intensify the tendency of Korean corporations to adopt high-risk and high return strategy in an economic downturn. Thus, firms might be able to use CEO narcissism to drastically restructure the business portfolio in an economic downturn. However, Korean corporations should be very cautions to maximize the positive effect of CEO narcissism. They might be use the institutional investors as their corporate governance system to monitor and control the opportunism of CEO in the decision for diversification in an economic downturn.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.133-149
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• 2014

One of the main purposes of universities is to create new intellectual resources that will increase social values. These intellectual resources include academic research papers, lecture notes, patents, and creative ideas produced by both professors and students. However, intellectual resources in universities are often not distributed to the actual users or companies; and moreover, they are not even systematically being managed inside of the universities. Therefore, it is almost impossible for companies to access the knowledge created by university students and professors to utilize them. Thus, the current level of knowledge sharing between universities and industries are very low. This causes a great extravagant with high-quality intellectual and human resources, and it leads to quite an amount of social loss in the modern society. In the 21st century, the creative ideas are the key growth powers for many industries. Many of the globally leading companies such as Fedex, Dell, and Facebook have established their business models based on the innovative ideas created by university students in undergraduate courses. This indicates that the unconventional ideas from young generations can create new growth power for companies and immensely increase social values. Therefore, this paper suggests of a new platform for intellectual properties distribution with university-industry cooperation. The suggested platform distributes intellectual resources of universities to industries. This platform has following characteristics. First, it distributes not only the intellectual resources, but also the human resources associated with the knowledge. Second, it diversifies the types of compensation for utilizing the intellectual properties, which are beneficial for both the university students and companies. For example, it extends the conventional monetary rewards to non-monetary rewards such as influencing on the participating internship programs or job interviews. Third, it suggests of a new knowledge map based on the relationships between key words, so that the various types of intellectual properties can be searched efficiently. In order to design the system platform, we surveyed 120 potential users to obtain the system requirements. First, 50 university students and 30 professors in humanities and social sciences departments were surveyed. We sent queries on what types of intellectual resources they produce per year, how many intellectual resources they produce, if they are willing to distribute their intellectual properties to the industries, and what types of compensations they expect in returns. Secondly, 40 entrepreneurs were surveyed, who are potential consumers of the intellectual properties of universities. We sent queries on what types of intellectual resources they want, what types of compensations they are willing to provide in returns, and what are the main factors they considered to be important when searching for the intellectual properties. The implications of this survey are as follows. First, entrepreneurs are willing to utilize intellectual properties created by both professors and students. They are more interested in creative ideas in universities rather than the academic papers or educational class materials. Second, non-monetary rewards, such as participating internship program or job interview, can be the appropriate types of compensations to replace monetary rewards. The results of the survey showed that majority of the university students were willing to provide their intellectual properties without any monetary rewards to earn the industrial networks with companies. Also, the entrepreneurs were willing to provide non-monetary compensation and hoped to have networks with university students for recruiting. Thus, the non-monetary rewards are mutually beneficial for both sides. Thirdly, classifying intellectual resources of universities based on the academic areas are inappropriate for efficient searching. Also, the various types of intellectual resources cannot be categorized into one standard. This paper suggests of a new platform for the distribution of intellectual materials and human resources, with university-industry cooperation based on these survey results. The suggested platform contains the four major components such as knowledge schema, knowledge map, system interface, and GUI (Graphic User Interface), and it presents the overall system architecture.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.6
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• pp.49-62
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• 2018

The purpose of this study is to develop an assessment index for the selection of promising start-ups, which will enhance the efficiency of program that support start-ups. In order to develop assessment models for selecting start-ups, three major research steps were conducted. First, this study attempted to theoretically redefine the assessment index from the perspective of the Balanced Scorecard (BSC) through a literature review. Second, major assessment index were derived using Delphi technique for experts in start-up areas. Third, weights were derived by applying AHP technique to calculate the importance of each index. The results of this study are summarized as follows. First, this study attempted to apply the assessment model for selecting start-ups from the Balanced Scorecard (BSC) view through the previous study review. Second, the final major questions were derived with sufficient opinions collected and structured survey of leading start-up experts in areas related to research subjects and elicited the most representative questions. Third, the results of applying the weights of the main selected assessment index, commercialization viewpoint is the most priority, followed by market view, technology development viewpoint, and organizational capability viewpoint. In the middle section, th ability to make products in the commercialization viewpoint, market competitiveness in the market, product discrimination capacity in the technology development perspective, and the ability of the entrepreneur in the organizational capacity perspective were important. Overall important items were found to be in the order of the capabilities of entrepreneurs, market competitiveness, product fire capability, and product discrimination. The importance of small items was highest priority for comparative excellence of competing products, and the degree of marketability, capacity of entrepreneurship, ability to raise capital, desire for entrepreneurship, and passion were shown. The results of this study presented a conceptual alternative to the preceding study on the development of existing selection assessment indexes. And it provides meaningful and important implications as an attempt to develop more sophisticated indicators by overcoming the limitations of empirical research on only some of the evaluation metrics.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.6
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• pp.177-196
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• 2021

In the era of the 4th industrial revolution, high technology is causing many changes in modern society and economy. Among them, changes in industries and jobs require new competencies of future human resources. As an educational alternative to these changes, maker education and design thinking methods are spreading around the world, and it is necessary to actively apply such education in university curriculum. Therefore, this study examines the effects of the maker education using the design thinking method on the learners' competencies required as future human resources and, relationship between the development of university students' entrepreneurial competencies and learners' competencies. And the purpose of this study is to contribute to the vitalization of entrepreneurship education for university students by suggesting an educational model. For this purpose, this study investigated the prior research on maker education/environment and design thinking methods to examine concepts and characteristics, and analyzed the influences between maker education/environment and design thinking methods and the development of learners' personal, social and technological capabilities. In addition, this study analyzed the relationship between learners' developed capabilities and university students' entrepreneurial capabilities, and based on the results, suggested directions and conceptual models for education that combine maker education/environment and design thinking methods. In conclusion, maker education/environment and design thinking methods in university education have a positive effect on the cognitive, social, and technological development of learners, and this has a significant relationship with the factors of personal, social, and technological dimensions of university students' entrepreneurial competency. It is analyzed that it has a positive effect on the promotion of entrepreneurship activities of university students. Therefore, it is judged that university's interest and support should be given to the vitalization of maker education using the design thinking method for university student entrepreneurship education and future human resources nurturing.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.145-165
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• 2023

Recommendation system plays a significant role on relieving difficulties of selecting information among rapidly increasing amount of information caused by the development of the Internet and on efficiently displaying information that fits individual personal interest. In particular, without the help of recommendation system, E-commerce and OTT companies cannot overcome the long-tail phenomenon, a phenomenon in which only popular products are consumed, as the number of products and contents are rapidly increasing. Therefore, the research on recommendation systems is being actively conducted to overcome the phenomenon and to provide information or contents that are aligned with users' individual interests, in order to induce customers to consume various products or contents. Usually, collaborative filtering which utilizes users' historical behavioral data shows better performance than contents-based filtering which utilizes users' preferred contents. However, collaborative filtering can suffer from cold-start problem which occurs when there is lack of users' historical behavioral data. In this paper, hybrid music recommendation system, which can solve cold-start problem, is proposed based on the playlist data of Melon music streaming service that is given by Kakao Arena for music playlist continuation competition. The goal of this research is to use music tracks, that are included in the playlists, and metadata of music tracks and playlists in order to predict other music tracks when the half or whole of the tracks are masked. Therefore, two different recommendation procedures were conducted depending on the two different situations. When music tracks are included in the playlist, LightFM is used in order to utilize the music track list of the playlists and metadata of each music tracks. Then, the result of Item2Vec model, which uses vector embeddings of music tracks, tags and titles for recommendation, is combined with the result of LightFM model to create final recommendation list. When there are no music tracks available in the playlists but only playlists' tags and titles are available, recommendation was made by finding similar playlists based on playlists vectors which was made by the aggregation of FastText pre-trained embedding vectors of tags and titles of each playlists. As a result, not only cold-start problem can be resolved, but also achieved better performance than ALS, BPR and Item2Vec by using the metadata of both music tracks and playlists. In addition, it was found that the LightFM model, which uses only artist information as an item feature, shows the best performance compared to other LightFM models which use other item features of music tracks.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.287-316
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• 2023

As global energy crisis and the COVID-19 pandemic have emerged as social issues, there is a growing demand for companies to move away from profit-centric business models and embrace sustainable management that balances environmental, social, and governance (ESG) factors. ESG activities of companies vary across industries, and industry-specific weights are applied in ESG evaluations. Therefore, it is important to develop strategic management approaches that reflect the characteristics of each industry and the importance of each ESG factor. Additionally, with the stance of strengthened focus on ESG disclosures, specific guidelines are needed to identify and report on sustainable management activities of domestic companies. To understand corporate sustainability strategies, analyzing ESG reports and news articles by industry can help identify strategic characteristics in specific industries. However, each company has its own unique strategies and report structures, making it difficult to grasp detailed trends or action items. In our study, we analyzed ESG reports (2019-2021) and news articles (2019-2022) of six companies in the 'Finance,' 'Manufacturing,' and 'IT' sectors to examine the sustainability strategies of leading domestic ESG companies. Text mining techniques such as keyword frequency analysis and topic modeling were applied to identify industry-specific, ESG element-specific management strategies and issues. The analysis revealed that in the 'Finance' sector, customer-centric management strategies and efforts to promote an inclusive culture within and outside the company were prominent. Strategies addressing climate change, such as carbon neutrality and expanding green finance, were also emphasized. In the 'Manufacturing' sector, the focus was on creating sustainable communities through occupational health and safety issues, sustainable supply chain management, low-carbon technology development, and eco-friendly investments to achieve carbon neutrality. In the 'IT' sector, there was a tendency to focus on technological innovation and digital responsibility to enhance social value through technology. Furthermore, the key issues identified in the ESG factors were as follows: under the 'Environmental' element, issues such as greenhouse gas and carbon emission management, industry-specific eco-friendly activities, and green partnerships were identified. Under the 'Social' element, key issues included social contribution activities through stakeholder engagement, supporting the growth and coexistence of members and partner companies, and enhancing customer value through stable service provision. Under the 'Governance' element, key issues were identified as strengthening board independence through the appointment of outside directors, risk management and communication for sustainable growth, and establishing transparent governance structures. The exploration of the relationship between ESG disclosures in reports and ESG issues in news articles revealed that the sustainability strategies disclosed in reports were aligned with the issues related to ESG disclosed in news articles. However, there was a tendency to strengthen ESG activities for prevention and improvement after negative media coverage that could have a negative impact on corporate image. Additionally, environmental issues were mentioned more frequently in news articles compared to ESG reports, with environmental-related keywords being emphasized in the 'Finance' sector in the reports. Thus, ESG reports and news articles shared some similarities in content due to the sharing of information sources. However, the impact of media coverage influenced the emphasis on specific sustainability strategies, and the extent of mentioning environmental issues varied across documents. Based on our study, the following contributions were derived. From a practical perspective, companies need to consider their characteristics and establish sustainability strategies that align with their capabilities and situations. From an academic perspective, unlike previous studies on ESG strategies, we present a subdivided methodology through analysis considering the industry-specific characteristics of companies.

• The Journal of Bigdata
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• v.8 no.1
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• pp.111-129
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• 2023

With the diffusion of digital innovation, the adoption of innovative medical technologies based on artificial intelligence is increasing in the medical field. This is driving the launch and adoption of AI-based SaMD(Software as a Medical Device), but there is a lack of research on the factors that influence the adoption of SaMD by medical institutions. The purpose of this study is to identify key factors that influence medical institutions' decisions to adopt AI-based SaMDs, and to analyze the weights and priorities of these factors. For this purpose, we conducted Delphi surveys based on the results of literature studies on technology acceptance models in healthcare industry, medical AI and SaMD, and developed a research model by combining HOTE(Human, Organization, Technology and Environment) framework and HABIO(Holistic Approach {Business, Information, Organizational}) framework. Based on the research model with 5 main criteria and 22 sub-criteria, we conducted an AHP(Analytical Hierarchy Process) analysis among the experts from domestic medical institutions and SaMD providers to empirically analyze SaMD adoption factors. The results of this study showed that the priority of the main criteria for determining the adoption of AI-based SaMD was in the order of technical factors, economic factors, human factors, organizational factors, and environmental factors. The priority of sub-criteria was in the order of reliability, cost reduction, medical staff's acceptance, safety, top management's support, security, and licensing & regulatory levels. Specifically, technical factors such as reliability, safety, and security were found to be the most important factors for SaMD adoption. In addition, the comparisons and analyses of the weights and priorities of each group showed that the weights and priorities of SaMD adoption factors varied by type of institution, type of medical institution, and type of job in the medical institution.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.915-929
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• 2023

Improvements in people's quality of life, diversification of leisure activities, and changes in population structure have led to an increase in the demand for tourism and an expansion of the diversification of tourism activities. In particular, for coastal cities where land and marine tourism elements coexist, various factors influence their tourism demands. Tourism requires the construction of infrastructure and content development according to the demand at the tourist destination. This study aims to improve the prediction accuracy and explore influencing factors through time series analysis of tourism scale using agent-based data. Basic local governments in the Busan area were examined, and the data used were the number of tourists and the amount of tourism consumption on a monthly basis. The univariate time series analysis, which is a deterministic model, was used along with the SARIMAX analysis to identify the influencing factor. The tourism consumption propensity, focusing on the consumption amount according to business types and the amount of mentions on SNS, was set as the influencing factor. The difference in accuracy (RMSE standard) between the time series models that did and did not consider COVID-19 was found to be very wide, ranging from 1.8 times to 32.7 times by region. Additionally, considering the influencing factor, the tourism consumption business type and SNS trends were found to significantly impact the number of tourists and the amount of tourism consumption. Therefore, to predict future demand, external influences as well as the tourists' consumption tendencies and interests in terms of local tourism must be considered. This study aimed to predict future tourism demand in a coastal city such as Busan and identify factors affecting tourism scale, thereby contributing to policy decision-making to prepare tourism demand in consideration of government tourism policies and tourism trends.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.2
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• pp.35-52
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• 2023

Recently, as the non-face-to-face environment has developed due to COVID-19 and environmental pollution, the importance of online digital healthcare is increasing, and venture start-ups and activities such as health care, telemedicine, and digital treatments are also actively underway. This study conducted the impact on the acceptability of digital healthcare smartwatches with an integrated approach of the expanded integrated technology acceptance model (UTAUT2) and the behavioral inference model (BRT). The most advanced integrated technology acceptance model for innovative technology acceptance research was used to identify major factors such as utility expectations, social effects, convenience, price barriers, lack of alternatives, and behavioral intentions. For the study, about 410 responses from ordinary people in their teens to 60s across the country were collected, and based on this, the hypothesis was verified using structural equations after testing reliability and validity of the data. SPSS 23 and AMOS 23 were used for research analysis. Studies have shown that personal innovation has a significant impact on the reasons for acceptance (use value, social impact, convenience of use), attitude, and non-use (price barriers, lack of alternatives, and barriers to use). These results are the same as the results of previous studies that confirmed the influence of the main value of innovative ICT on user acceptance intention. In addition, the reason for acceptance had a significant effect on attitude, but the effect of the reason for non-acceptance was not significant. It can be analyzed that consumers are interested in new ICT products and new services, but purchase them more carefully and selectively. This study has evolved from the acceptance analysis of general-purpose consumer innovation technology to the acceptance analysis of consumer value in smartwatch digital healthcare, which is a new and important area in the future. Industrially, it can contribute to the product's purchase and marketing. It is hoped that this study will contribute to increasing research in the digital healthcare sector, which will play an important role in our lives in the future, and that it will develop into in-depth factors that are more suitable for consumer value through integrated approach models and integrated analysis of consumer acceptance and non-acceptance.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.21-35
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• 2023

Expectations surrounding generative AI technology and its profound ramifications are sweeping across various industrial domains. Given the anticipated pivotal role of the startup ecosystem in the utilization and advancement of generative AI technology, it is imperative to cultivate a deeper comprehension of the present state and distinctive attributes characterizing venture capital (VC) investments within this domain. The current investigation delves into South Korea's landscape of VC investment deals and prognosticates the projected VC investments by juxtaposing these against the United States, the frontrunner in the generative AI industry and its associated ecosystem. For analytical purposes, a compilation of 286 investment deals originating from 117 U.S. generative AI startups spanning the period from 2008 to 2023, as well as 144 investment deals from 42 South Korean generative AI startups covering the years 2011 to 2023, was amassed to construct new datasets. The outcomes of this endeavor reveal an upward trajectory in the count of VC investment deals within both the U.S. and South Korea during recent years. Predominantly, these deals have been concentrated within the early-stage investment realm. Noteworthy disparities between the two nations have also come to light. Specifically, in the U.S., in contrast to South Korea, the quantum of recent VC deals has escalated, marking an augmentation ranging from 285% to 488% in the corresponding developmental stage. While the interval between disparate investment stages demonstrated a slight elongation in South Korea relative to the U.S., this discrepancy did not achieve statistical significance. Furthermore, the proportion of VC investments channeled into generative AI enterprises, relative to the aggregate number of deals, exhibited a higher quotient in South Korea compared to the U.S. Upon a comprehensive sectoral breakdown of generative AI, it was discerned that within the U.S., 59.2% of total deals were concentrated in the text and model sectors, whereas in South Korea, 61.9% of deals centered around the video, image, and chat sectors. Through forecasting, the anticipated VC investments in South Korea from 2023 to 2029 were derived via four distinct models, culminating in an estimated average requirement of 3.4 trillion Korean won (ranging from at least 2.408 trillion won to a maximum of 5.919 trillion won). This research bears pragmatic significance as it methodically dissects VC investments within the generative AI domain across both the U.S. and South Korea, culminating in the presentation of an estimated VC investment projection for the latter. Furthermore, its academic significance lies in laying the groundwork for prospective scholarly inquiries by dissecting the current landscape of generative AI VC investments, a sphere that has hitherto remained void of rigorous academic investigation supported by empirical data. Additionally, the study introduces two innovative methodologies for the prediction of VC investment sums. Upon broader integration, application, and refinement of these methodologies within diverse academic explorations, they stand poised to enhance the prognosticative capacity pertaining to VC investment costs.